AI Fundamentals for Security Professionals

This is an official ISACA course, it introduces you to the fundamental topics of Artificial Intelligence (AI), essential for every security professional, a growing and rapidly changing field that is becoming increasingly vital to business survival, job stability, and national security.

The ISACA Artificial Intelligence Fundamentals Certificate is intended for a wide-range of individuals, including:

• IT Audit, Risk, Security and Governance professionals looking to gain a fundamental understanding of emerging technology knowledge and skills.
• Those new to IT, students, recent graduates and career changers looking to differentiate themselves from other job candidates.
• Current IT Professionals looking to upskill to broaden their IT knowledge and skills or keep up-to-date with emerging technologies.

This course is not a technical security course and does not cover generative AI ‘prompt’ security engineering.

Session 1 Learning Objectives

• Explain the basics of AI
• Describe properties of AI
• Identify resource requirements for adopting AI
• Articulate expert systems (e.g., temporal reasoning, logic and inference)
• Distinguish machine learning models (e.g., decision trees, regression models, Bayesian)

Session 2 Learning Objectives

• Describe machine learning algorithms (e.g., supervised learning, unsupervised learning, deep learning)
• Describe enterprise usage of artificial intelligence (e.g., RPA, log analysis, image processing, NLP, fraud detection, cybersecurity, healthcare)
• Identify consumer usage of artificial intelligence (e.g., autonomous vehicles, digital assistants, freelance mobile marketplace)
• Identify risks associated with artificial intelligence (e.g., cybersecurity, privacy, data loss)
• Articulate ethical dilemmas in artificial intelligence (e.g., privacy, bias, nefarious usage)

No prequisites

Course Topics Include:

Session 1 Topics:

• Properties of Artificial Intelligence Condensed version
• Resource Requirements for Adopting AI
• Expert Systems
• Machine Learning Models

Session 2 Topics:

• Statistical Modeling
• Machine Learning Algorithms
• Enterprise Usage of Artificial Intelligence
• Consumer Usage of Artificial Intelligence
• Risks Associated with Artificial Intelligence
• Ethics in Artificial Intelligence